mlsanityData to 7 Oct 2026

ACE: A LLM-based Negotiation Coaching System

arXiv 2410.01555 ↗First posted 2 Oct 2024cs.CL cs.HCcited by 13

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Abstract (arXiv)

The growing prominence of LLMs has led to an increase in the development of AI tutoring systems. These systems are crucial in providing underrepresented populations with improved access to valuable education. One important area of education that is unavailable to many learners is strategic bargaining related to negotiation. To address this, we develop a LLM-based Assistant for Coaching nEgotiation (ACE). ACE not only serves as a negotiation partner for users but also provides them with targeted feedback for improvement. To build our system, we collect a dataset of negotiation transcripts between MBA students. These transcripts come from trained negotiators and emulate realistic bargaining scenarios. We use the dataset, along with expert consultations, to design an annotation scheme for detecting negotiation mistakes. ACE employs this scheme to identify mistakes and provide targeted feedback to users. To test the effectiveness of ACE-generated feedback, we conducted a user experiment with two consecutive trials of negotiation and found that it improves negotiation performances significantly compared to a system that doesn't provide feedback and one which uses an alternative method of providing feedback.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 12 of its 32 references that are in the map. First posted on arXiv 2 Oct 2024.

Builds on

12 of 32 references.

References · 12

  1. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
  2. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 3,972
  3. 2017Deal or No Deal? End-to-End Learning for Negotiation Dialoguescited by 202
  4. 2023Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedbackcited by 202
  5. 2018Decoupling Strategy and Generation in Negotiation Dialoguescited by 156
  6. 2024How Well Can LLMs Negotiate? NegotiationArena Platform and Analysiscited by 93
  7. 2023CLASS: A Design Framework for building Intelligent Tutoring Systems based on Learning Science principlescited by 46
  8. 2023Large Language Models (GPT) for automating feedback on programming assignmentscited by 32
  9. 2022Let's Negotiate! A Survey of Negotiation Dialogue Systemscited by 31
  10. 2023Prompt Problems: A New Programming Exercise for the Generative AI Eracited by 31
  11. 2024Open Source Language Models Can Provide Feedback: Evaluating LLMs' Ability to Help Students Using GPT-4-As-A-Judgecited by 19
  12. 2023Negotiating with LLMS: Prompt Hacks, Skill Gaps, and Reasoning Deficitscited by 16

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 6; 2026: 6.

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  1. 2025The Automated but Risky Game: Modeling and Benchmarking Agent-to-Agent Negotiations and Transactions in Consumer Marketscited by 12
  2. 2025EvoEmo: Towards Evolved Emotional Policies for Adversarial LLM Agents in Multi-Turn Price Negotiationcited by 8
  3. 2025Advancing AI Negotiations: A Large-Scale Autonomous Negotiation Competitioncited by 6
  4. 2024Leveraging Large Language Models for Active Merchant Non-player Characterscited by 4
  5. 2025ASTRA: A Negotiation Agent with Adaptive and Strategic Reasoning via Tool-integrated Action for Dynamic Offer Optimizationcited by 4
  6. 2025KoACD: The First Korean Adolescent Dataset for Cognitive Distortion Analysis via Role-Switching Multi-LLM Negotiationcited by 4
  7. 2025Does AI Coaching Prepare us for Workplace Negotiations?cited by 2
  8. 2026MERIT Feedback Elicits Better Bargaining in LLM Negotiatorscited by 2
  9. 2026Not My Truce: Personality Differences in AI-Mediated Workplace Negotiationcited by 2
  10. 2026The Language of Bargaining: Linguistic Effects in LLM Negotiationscited by 0
  11. 2026EmoDistill: Offline Emotion Skill Distillation for Language Model Agents in Adversarial Negotiationcited by 0
  12. 2026Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studiescited by 0
1 more
  1. 2026DIPLOMAT: Dialogue-Span-Aware Direct Preference Optimization for Polite Persuasive Workplace Negotiation Dialoguescited by 0